Biology subjects

Fleishman, S. J.

Publications and source records attributed to Fleishman, S. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Combining Stability-Centered Atomistic Design with Machine Learning for Targeted Enzyme Optimization

FuncLib and high-throughput FuncLib (htFuncLib) generate diverse, functional protein libraries using a stability-centered design; however, this substrate-independent approach lacks target-specific functional constraints. We developed a machine-learning-assisted enzyme-engineering (MLEE) workflow that adds substrate-specific functional information to htFuncLib through an initial screening and sequencing round. The system was benchmarked using previously published four-position fitness landscapes of three different proteins. The MLEE workflow successfully generated compact libraries enriched in globally high-fitness variants. After the initial training phase, an MLEE-enriched library of just 12 variants increased the hit rate for the global top-0.05% variants by 5- to 12-fold relative to the htFuncLib baseline. Screening a larger set of 96 variants recovered at least one of these top-performing enzymes in 61.3-99.4% of the simulations. We then applied MLEE to MthUPO-catalyzed {beta}-damascone hydroxylation. Across two rounds, 506 distinct variants were screened and sequenced. While the initial substrate-independent htFuncLib library yielded 14% of variants with activity above the wild type, the MLEE-enriched library increased this hit rate to 90% (97 of 108 variants) with activity above the wild type. The best variant increased the turnover number for 4-hydroxy-{beta}-damascone by 11.8-fold and achieved >99% regioisomeric excess. MLEE may bypass the need for transition-state models and reduce the effort required for obtaining high-activity variants. TABLE OF CONTENT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/739108v1_ufig1.gif" ALT="Figure 1"> View larger version (18K): org.highwire.dtl.DTLVardef@1501d4aorg.highwire.dtl.DTLVardef@b32171org.highwire.dtl.DTLVardef@58b249org.highwire.dtl.DTLVardef@120f8a6_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2026

Nanobodies against Plasmodium adhesins that block receptor engagement and malaria parasite invasion

Malaria is caused by Plasmodium parasites, and its clinical symptoms are a result of parasite invasion of red blood cells and the subsequent cycles of replication and proliferation. In human populations, Plasmodium vivax is responsible for the most widely distributed recurring malaria infections whereas Plasmodium falciparum inflicts the most mortality and morbidity. One well-characterized family of adhesins involved in red blood cell invasion is the reticulocyte-binding-like protein homolog family, known as the RBL superfamily which includes the PfRh family in P. falciparum and PvRBP family in P. vivax. Here we report a collection of nanobodies against three members of this adhesin family, PfRh5, PfRh4 and PvRBP2b. Nanobodies against these Plasmodium adhesins bind with high affinity across several epitopes and can block receptor engagement and inhibit parasite invasion of red blood cells. Using computational design, we generated stabilized PfRh4 variants that encompass the conserved scaffold present in the PfRh and PvRBP families of adhesins and show that several variants with improved expression retained binding to mouse monoclonal antibodies, nanobodies and Complement Receptor 1, the human receptor for PfRh4. We also observed that most of the inhibitory nanobodies against the three antigens recognized the conserved structural scaffold that define this family of adhesins. These results demonstrate the potential of nanobodies to block malaria parasite invasion into red blood cells.

microbiology↗

bioRxiv2026

Simple baselines rival protein language models in mutation-dense design tasks

Computational protein design demands generally applicable models that reliably predict or generate unmeasured variants with superior functional properties. Although protein language models (pLMs) have been used in zero-shot and transfer-learning design studies, they have generally not been assessed in benchmarks that explicitly test combinatorial extrapolation from lower- to higher-order variants. Here we benchmark widely used pLMs against conventional baseline methods in recently described dense, experimentally validated multi-mutant landscapes. We find that regardless of architecture and parameter count, pLMs are statistically similar to one another, and none consistently outperforms conventional baseline methods. Furthermore, their ability to distinguish functional from non-functional variants in zero-shot prediction is comparable to that of conventional homology-based methods. We suggest that to contribute significantly to the design of protein function, pLMs may need to encode biophysical and structural priors or be combined with structure-based approaches.

bioinformatics↗

bioRxiv2025

Structure-based design of antibody repertoires with drug-like properties

Animal immunization is the prevalent strategy for discovering antibody therapeutics1, but it is a lengthy and poorly controlled process. As an alternative, synthetic antibody repertoires deliver antibodies without animal welfare concerns, but the resulting antibodies often fail to exhibit "drug-like" biophysical properties1,2. Modern repertoires have improved developability by using a handful of frameworks with desirable biophysical properties, but at the cost of reduced structural diversity3-6. We developed a principled structure- and energy-based strategy, called CADAbRe, to navigate the complex tradeoffs between developability and structural diversity in repertoire design. The designed repertoire comprises billions of antibodies that are predicted to be stable and foldable, built from hundreds of different frameworks and hundreds of thousands of designed CDR H3s. We also developed an economical and scalable strategy for synthesizing large antibody repertoires, and as a proof of concept, designed and synthesized a 500-million variant phage display repertoire. Selections against four unrelated targets produced structurally diverse binders that exhibited drug-like properties, two of which were readily formatted as bispecifics for functional studies. Furthermore, one of the binders targets a challenging, highly charged surface. The proof-of-concept repertoire is available for academic research. We envision that the CADAbRe approach and repertoire will accelerate and rationalize antibody discovery while addressing animal-welfare concerns7.

synthetic biology↗

bioRxiv2025

Energy-guided combinatorial co-optimization of antibody affinity and stability

Affinity maturation is an essential process in antibody engineering. Although powerful, it is iterative, time-consuming, and can result in trade-offs, where affinity is gained at the cost of important properties, such as specificity and stability. We present a scalable strategy, called LAffAb, that starts from a crystallographic structure of the antibody-antigen complex and introduces combinations of mutations to optimize its energy. A combinatorial library comprising 7,000 variants with up to nine mutations results in gains of up to 30-fold in affinity while co-optimizing stability. Surprisingly, the library does not converge on a single solution, instead favoring diverse variants with a high mutational load. Small-scale screening of 10 designs against a potential drug target results in an order-of-magnitude improvement in affinity while maintaining high developability. We also apply LAffAb to improve the developability of a therapeutic antibody without degrading affinity. We envision that LAffAb can be used to design stable, specific, and high-affinity binders and to improve our understanding of sequence, structure, and function relationships in antibodies.

synthetic biology↗

bioRxiv2025

High-efficiency Kemp eliminases by complete computational design

We present a fully computational workflow for de novo design of efficient enzymes using backbone fragments from natural proteins and without recourse to iterative experimental optimization. The best designed Kemp eliminase exhibits >140 mutations from any natural protein, high stability (>85 {degrees}C) and unprecedented catalytic efficiency (12,700 M-1s-1), surpassing previous computational designs by two orders of magnitude. We find that mutations both inside and outside the active site contribute synergistically to the high observed activity and stability. Mutation of an aromatic residue used in all prior Kemp eliminase designs increases efficiency to >105 M-1s-1. Our approach addresses critical limitations in design methodology, generating stable, high-efficiency, new-to-nature enzymes in complex folds and enables testing hypotheses on the fundamentals of biocatalysis through a limited experimental effort.

biochemistry↗

bioRxiv2024

Preclinical Development of a Stabilized RH5 Virus-Like Particle Vaccine that Induces Improved Anti-Malarial Antibodies

The development of a highly effective vaccine against the pathogenic blood-stage infection of human malaria will require a delivery platform that can induce an antibody response of both maximal quantity and functional quality. One strategy to achieve this includes presenting antigens to the immune system on virus-like particles (VLPs). Here we sought to improve the design and delivery of the blood-stage Plasmodium falciparum reticulocyte-binding protein homolog 5 (RH5) antigen, which is currently in a Phase 2 clinical trial as a full-length soluble protein-in-adjuvant vaccine candidate called RH5.1/Matrix-M. We identify disordered regions of the full-length RH5 molecule induce non-growth inhibitory antibodies in human vaccinees, and a re-engineered and stabilized immunogen that includes just the alpha-helical core of RH5 induces a qualitatively superior growth-inhibitory antibody response in rats vaccinated with this protein formulated in Matrix-M adjuvant. In parallel, bioconjugation of this new immunogen, termed "RH5.2", to hepatitis B surface antigen VLPs using the "plug-and-display" SpyTag-SpyCatcher platform technology also enabled superior quantitative antibody immunogenicity over soluble antigen/adjuvant in vaccinated mice and rats. These studies identify a new blood-stage malaria vaccine candidate that may improve upon the current leading soluble protein vaccine candidate RH5.1/Matrix-M. The RH5.2-VLP/Matrix-M vaccine candidate is now under evaluation in Phase 1a/b clinical trials.

immunology↗

bioRxiv2023

GGAssembler: Economical Design of Gene Libraries with Precise Control over Mutations

Golden Gate assembly (GGA) can seamlessly generate full-length genes from DNA fragments. In principle, GGA could be used to design combinatorial mutation libraries for protein engineering, but creating accurate, complex, and cost-effective libraries has been challenging. We present GGAssembler, a graph-theoretical method for economical design of DNA fragments that assemble a combinatorial library that encodes any desired diversity. We used GGAssembler for one-pot in vitro assembly of camelid antibody libraries comprising >105 variants with DNA costs <0.007$ per variant and dropping significantly with increased library complexity. >93% of the desired variants were present in the assembly product and >99% were represented within the expected order of magnitude as verified by deep sequencing. The GGAssembler workflow is, therefore, an accurate approach for generating complex variant libraries that may drastically reduce costs and accelerate discovery and optimization of antibodies, enzymes and other proteins. The workflow is accessible through a web interface at https://github.com/Fleishman-Lab/GGAssembler/blob/master/example/colab_oligos_design.ipynb.

molecular biology↗

bioRxiv2023

Stable mammalian serum albumins designed for bacterial expression

Albumin is the most abundant protein in the blood serum of mammals and has essential carrier and physiological roles. Albumins are also used in a wide variety of molecular and cellular experiments and in the cultivated meat industry. Despite their importance, however, albumins are challenging for heterologous expression in microbial hosts, likely due to 17 conserved intramolecular disulfide bonds. Therefore, albumins used in research and biotechnological applications either derive from animal serum, despite severe ethical and reproducibility concerns, or from recombinant expression in yeast or rice. We use the PROSS algorithm to stabilize human and bovine serum albumins, finding that all are highly expressed in E. coli. Design accuracy is verified by crystallographic analysis of a human albumin variant with 16 mutations. This albumin variant exhibits ligand binding properties similar to those of the wild type. Remarkably, a design with 73 mutations relative to human albumin exhibits over 40{degrees}C improved stability and is stable beyond the boiling point of water. Our results suggest that proteins with many disulfide bridges have the potential to exhibit extreme stability when subjected to design. The designed albumins may be used to make economical, reproducible, and animal-free reagents for molecular and cell biology. They also open the way to high-throughput screening to study and enhance albumin carrier properties. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/534334v3_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@71ef93org.highwire.dtl.DTLVardef@27a975org.highwire.dtl.DTLVardef@1e657fforg.highwire.dtl.DTLVardef@19b3de3_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- Computational design stabilized human and bovine serum albumins - Designs express solubly in E. coli and exhibit up to 40 {degrees}C increased thermostability - Some designs exhibit identical ligand binding properties - Crystal structure confirms design accuracy - Designs can be used in cell culture and in vitro applications

biochemistry↗

bioRxiv2022

One-shot design elevates functional expression levels of a voltage-gated potassium channel

Membrane proteins play critical physiological roles as receptors, channels, pumps, and transporters. Despite their importance, however, low expression levels often hamper the experimental characterization of membrane proteins. We present an automated and web-accessible design algorithm called mPROSS (https://mPROSS.weizmann.ac.il), which uses phylogenetic analysis and an atomistic potential, including an empirical lipophilicity scale, to improve native-state energy. As a stringent test, we apply mPROSS to the Kv1.2-Kv2.1 paddle chimera voltage-gated potassium channel. Four designs, encoding 9-26 mutations relative to the parental channel, were functional and maintained potassium-selective permeation and voltage dependence in Xenopus oocytes with up to 14-fold increase in whole-cell current densities. Additionally, single-channel recordings reveal no significant change in the channel-opening probability nor in unitary conductance, indicating that functional expression levels increase without impacting the activity profile of individual channels. Our results suggest that the expression levels of other dynamical channels and receptors may be enhanced through one-shot design calculations. Significance statementHeterologous expression levels of membrane proteins are often low, limiting research and applications. We combine homologous-sequence analysis with Rosetta atomistic calculations to enable one-shot design of dozens of mutations that improve native-state energy. Applied to a voltage-gated potassium channel, designs exhibited up to 14-fold improved functional expression levels in oocytes with almost no change in the single-channel activity profile. This design approach may accelerate research of many challenging membrane proteins, including receptors, channels, and transporters.

biochemistry↗

bioRxiv2022

Designed active-site library reveals thousands of functional GFP variants

Mutations in a protein active site can lead to dramatic and useful changes in protein activity. The active site, however, is extremely sensitive to mutations due to a high density of molecular interactions, drastically reducing the likelihood of obtaining functional multipoint mutants. We introduce an atomistic and machine-learning-based approach, called htFuncLib, to design a sequence space in which mutations form low-energy combinations that mitigate the risk of incompatible interactions. We applied htFuncLib to the GFP chromophore-binding pocket, and, using fluorescence readout, recovered >16,000 unique designs encoding as many as eight active-site mutations. Many designs exhibit substantial and useful diversity in functional thermostability (up to 96 {degrees}C), fluorescence lifetime, and quantum yield. By eliminating incompatible active-site mutations, htFuncLib generates a large diversity of functional sequences. We envision that htFuncLib will be useful for one-shot optimization of activity in enzymes, binders, and other proteins.

biochemistry↗

bioRxiv2022

Modularly designed protein fragments combine into thousands of active and structurally diverse enzymes

Design of structurally diverse enzymes is constrained by long-range interactions that are needed for accurate folding. We introduce an atomistic and machine-learning strategy for Combinatorial Assembly and Design of ENZymes, CADENZ, to design fragments that combine with one another to generate diverse, low-energy structures with stable catalytic constellations. We applied CADENZ to endoxylanases and used activity-based protein profiling to recover thousands of active and structurally diverse enzymes. Functional designs exhibit high active-site preorganization and more stable and compact packing outside the active site. Implementing these lessons into CADENZ led to a tenfold improved hit rate and >10,000 active enzymes. This design-test-learn loop can be applied, in principle, to any modular protein family, yielding huge diversity and general lessons on protein design principles.

bioengineering↗

bioRxiv2022

Reliable energy-based antibody humanization and stabilization

Humanization is an essential step in developing animal-derived antibodies into therapeutics, and approximately one third of approved antibodies have been humanized. Conventional humanization approaches graft the complementarity-determining regions (CDRs) of the animal antibody onto several homologous human frameworks. This process, however, often drastically lowers stability and antigen binding, demanding iterative mutational fine-tuning to recover the original antibody properties. Here, we present Computational hUMan AntiBody design (CUMAb), a web-accessible method that starts from an experimental or model antibody structure, systematically grafts the animal CDRs on thousands of human frameworks, and uses Rosetta atomistic simulations to rank the designs by energy and structural integrity (http://CUMAb.weizmann.ac.il). CUMAb designs of five independent antibodies exhibit similar affinities to the parental animal antibody, and some designs show marked improvement in stability. Surprisingly, nonhomologous frameworks are often preferred to the highest-homology ones, and several CUMAb designs that use different human frameworks and differ by dozens of mutations are functionally equivalent. Thus, CUMAb presents a general and streamlined approach to optimizing antibody stability and expressibility while increasing humanness.

bioengineering↗

bioRxiv2022

Designed high-redox potential laccases exhibit high functional diversity

White-rot fungi secrete an impressive repertoire of high-redox potential laccases (HRPLs) and peroxidases for efficient oxidation and utilization of lignin. Laccases are attractive enzymes for green-chemistry applications due to their broad substrate range and low environmental impact. Since expression of functional recombinant HRPLs is challenging, however, iterative directed evolution protocols have been applied to improve their expression, activity and stability. We implement a rational, stabilize-and-diversify strategy to two HRPLs that we could not functionally express: first, we use the PROSS stability-design algorithm to allow functional expression in yeast. Second, we use the stabilized enzymes as starting points for FuncLib active-site design to improve their activity and substrate diversity. Four of the FuncLib designed HRPLs and their PROSS progenitor exhibit substantial diversity in reactivity profiles against high-redox potential substrates, including lignin monomers. Combinations of 3-4 subtle mutations that change the polarity, solvation and sterics of the substrate-oxidation site result in orders of magnitude changes in reactivity profiles. These stable and versatile HRPLs are a step towards the generation of an effective lignin-degrading consortium of enzymes that can be secreted from yeast. More broadly, the stabilize-and-diversify strategy can be applied to other challenging enzyme families to study and expand the utility of natural enzymes.

biochemistry↗

bioRxiv2022

Protein Quaternary Structures in Solution are a Mixture of Multiple forms

Over half the proteins form homo or hetero-oligomeric structures. Experimentally determined structures are often considered in determining a proteins oligomeric state, but static structures miss the dynamic equilibrium between different quaternary forms. The problem is exacerbated in homo-oligomers, where the oligomeric states are challenging to characterize. Here, we re-evaluated the oligomeric state of 17 different bacterial proteins across a broad range of protein concentrations and solutions by native mass-spectrometry (MS), mass photometry (MP), size exclusion chromatography (SEC), and small-angle x-ray scattering (SAXS), finding that most exhibit several oligomeric states. Surprisingly, many proteins did not show mass-action driven equilibrium between the oligomeric states. For approximately half the proteins, the predicted oligomeric forms described in publicly available databases underestimated the complexity of protein quaternary structures in solution. Conversely, AlphaFold Multimer provided an accurate description of the potential multimeric states for most proteins, suggesting that it could help resolve uncertainties on the solution state of many proteins.

biochemistry↗

bioRxiv2021

Stable and functionally diverse versatile peroxidases by computational design directly from sequence

White-rot fungi secrete a repertoire of high-redox potential oxidoreductases to efficiently decompose lignin. Of these enzymes, versatile peroxidases (VPs) are the most promiscuous biocatalysts. VPs are attractive enzymes for research and industrial use, but their recombinant production is extremely challenging. To date, only a single VP has been structurally characterized and optimized for recombinant functional expression, stability and activity. Computational enzyme optimization methods can be applied to many enzymes in parallel, but they require accurate structures. Here, we demonstrate that model structures computed by deep-learning based ab initio structure prediction methods are reliable starting points for one-shot PROSS stability-design calculations. Four designed VPs encoding as many as 43 mutations relative to the wild type enzymes are functionally expressed in yeast whereas their wild type parents are not. Three of these designs exhibit substantial and useful diversity in reactivity profile and tolerance to environmental conditions. The reliability of the new generation of structure predictors and design methods increases the scale and scope of computational enzyme optimization, enabling efficient discovery and exploitation of the functional diversity in natural enzyme families.

biochemistry↗

bioRxiv2021

Stabilization of the SARS-CoV-2 Receptor Binding Domain by Protein Core Redesign and Deep Mutational Scanning

Stabilizing antigenic proteins as vaccine immunogens or diagnostic reagents is a stringent case of protein engineering and design as the exterior surface must maintain recognition by receptor(s) and antigen--specific antibodies at multiple distinct epitopes. This is a challenge, as stability-enhancing mutations must be focused on the protein core, whereas successful computational stabilization algorithms typically select mutations at solvent-facing positions. In this study we report the stabilization of SARS-CoV-2 Wuhan Hu-1 Spike receptor binding domain (S RBD) using a combination of deep mutational scanning and computational design, including the FuncLib algorithm. Our most successful design encodes I358F, Y365W, T430I, and I513L RBD mutations, maintains recognition by the receptor ACE2 and a panel of different anti-RBD monoclonal antibodies, is between 1-2{degrees}C more thermally stable than the original RBD using a thermal shift assay, and is less proteolytically sensitive to chymotrypsin and thermolysin than the original RBD. Our approach could be applied to the computational stabilization of a wide range of proteins without requiring detailed knowledge of active sites or binding epitopes, particularly powerful for cases when there are multiple or unknown binding sites.

biochemistry↗

bioRxiv2021

Assessing and enhancing foldability in designed proteins

Recent advances in protein-design methodology have led to a dramatic increase in reliability and scale. With these advances, dozens and even thousands of designed proteins are automatically generated and screened. Nevertheless, the success rate, particularly in design of functional proteins, is low and fundamental goals such as reliable de novo design of efficient enzymes remain beyond reach. Experimental analyses have consistently indicated that a major reason for design failure is inaccuracy and misfolding relative to the design model. To address this challenge, we describe complementary methods to diagnose and ameliorate suboptimal regions in designed proteins: first, we develop a Rosetta atomistic computational mutation scanning approach to detect energetically suboptimal positions in designs (available on a web server https://pSUFER.weizmann.ac.il); second, we demonstrate that AlphaFold2 ab initio structure prediction flags regions that may misfold in designed enzymes and binders; and third, we focus FuncLib design calculations on suboptimal positions in a previously designed low-efficiency enzyme improving its catalytic efficiency by 330 fold. Furthermore, applied to a de novo designed protein that exhibited limited stability, the same approach markedly improved stability and expressibility. Thus, foldability analysis and enhancement may dramatically increase the success rate in design of functional proteins.

biochemistry↗